Estimating the normal-inverse-Wishart distribution
Statistics Theory
2024-06-04 v2 Machine Learning
Machine Learning
Statistics Theory
Abstract
The normal-inverse-Wishart (NIW) distribution is commonly used as a prior distribution for the mean and covariance parameters of a multivariate normal distribution. The family of NIW distributions is also a minimal exponential family. In this short note we describe a convergent procedure for converting from mean parameters to natural parameters in the NIW family, or -- equivalently -- for performing maximum likelihood estimation of the natural parameters given observed sufficient statistics. This is needed, for example, when using a NIW base family in expectation propagation.
Keywords
Cite
@article{arxiv.2405.16088,
title = {Estimating the normal-inverse-Wishart distribution},
author = {Jonathan So},
journal= {arXiv preprint arXiv:2405.16088},
year = {2024}
}